Stochastic frontier estimation through parametric modelling of quantile regression coefficients

نویسندگان

چکیده

Abstract Stochastic frontiers are a very popular tool used to compare production units in terms of efficiency. The parameters this class models usually estimated through the use classic maximum likelihood method even, last years, some authors suggested conceive and estimate productive frontier within quantile regression framework. main advantages approach lie weaker assumptions about data distribution greater robustness presence outliers respect approach. However, empirical evidence theoretical contributions have highlighted that applied tails conditional distribution, namely frontiers, suffers from instability estimates needs specific tools approaches. To avoid limitation, we propose model stochastic as function order smooth its trend and, consequently, reduce instability. has been illustrated using real simulated experiments confirming good efficiency properties proposed method.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Stochastic Non-Parametric Frontier Analysis

In this paper we develop an approach that synthesizes the best features of the two main methods in the estimation of production efficiency. Specically, our approach first allows for statistical noise, similar to Stochastic frontier analysis, and second, it allows modeling multiple-inputs-multiple-outputs technologies without imposing parametric assumptions on production relationship, similar to...

متن کامل

Flexible parametric quantile regression model

This article introduces regression quantile models using both RS and FKML generalised lambda distributions (GLD) and demonstrates the versatility of proposed models for a range of linear/non linear and heteroscedastic/homoscedastic empirical data. Owing to the rich shapes of GLDs, GLD quantile regression is a competitive flexible model compared to standard quantile regression. The proposed meth...

متن کامل

Semi-parametric Quantile Regression for Analysing Continuous Longitudinal Responses

Recently, quantile regression (QR) models are often applied for longitudinal data analysis. When the distribution of responses seems to be skew and asymmetric due to outliers and heavy-tails, QR models may work suitably. In this paper, a semi-parametric quantile regression model is developed for analysing continuous longitudinal responses. The error term's distribution is assumed to be Asymmetr...

متن کامل

Censored Quantile Regression with Varying Coefficients

We propose a varying-coefficient quantile regression model for survival data subject to random censoring. Motivated by the work of Yang (1999), quantilebased moments are constructed using covariate-weighted empirical cumulative hazard functions. We estimate regression parameters based on the generalized method of moments. The proposed estimators are shown to be consistent and asymptotically nor...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Empirical Economics

سال: 2022

ISSN: ['1435-8921', '0377-7332']

DOI: https://doi.org/10.1007/s00181-022-02273-x